The field of the invention is magnetic resonance imaging (“MRI”) methods and systems. More particularly, the invention relates to methods and systems for simultaneous multi-slice MRI, in which either a single or multiple channel receiver coil is employed to simultaneously acquire image data from multiple slice locations.
MRI uses the nuclear magnetic resonance (“NMR”) phenomenon to produce images. When a substance such as human tissue is subjected to a uniform magnetic field (polarizing field B0), the individual magnetic moments of the nuclei in the tissue attempt to align with this polarizing field, but precess about it in random order at their characteristic Larmor frequency. If the substance, or tissue, is subjected to a magnetic field (excitation field B1) that is in the x-y plane and that is near the Larmor frequency, the net aligned moment, Mz, may be rotated, or “tipped,” into the x-y plane to produce a net transverse magnetic moment, Mxy. A signal is emitted by the excited nuclei or “spins,” after the excitation signal B1 is terminated, and this signal may be received and processed to form an image.
When utilizing these “MR” signals to produce images, magnetic field gradients (Gx, Gy, and Gz) are employed for the spatial encoding of the signals. Typically, the region to be imaged is scanned by a sequence of measurement cycles in which these gradients vary according to the particular localization method being used. The resulting set of received MR signals are digitized and processed to reconstruct the image using one of many well known reconstruction techniques.
The measurement cycle used to acquire each MR signal is performed under the direction of a pulse sequence produced by a pulse sequencer. Clinically available MRI systems store a library of such pulse sequences that can be prescribed to meet the needs of many different clinical applications. Research MRI systems include a library of clinically-proven pulse sequences and they also enable the development of new pulse sequences.
The MR signals acquired with an MRI system are signal samples of the subject of the examination in Fourier space, or what is often referred to in the art as “k-space.” Each MR measurement cycle, or pulse sequence, typically samples a portion of k-space along a sampling trajectory characteristic of that pulse sequence. Most pulse sequences sample k-space in a raster scan-like pattern sometimes referred to as a “spin-warp,” a “Fourier,” a “rectilinear,” or a “Cartesian” scan; however, other pulse sequences may sample k-space along non-Cartesian trajectories such as radial lines and spirals.
Depending on the technique used, many MR scans currently require many minutes to acquire the necessary data used to produce medical images. The reduction of this scan time is an important consideration, since reduced scan time increases patient throughout, improves patient comfort, and improves image quality by reducing motion artifacts. Many different strategies have been developed to shorten the scan time.
One such strategy for shortening scan time is referred to generally as “parallel MRI” (“pMRI”). Parallel MRI techniques use spatial information from arrays of radio frequency (“RF”) receiver coils to substitute for the spatial encoding that would otherwise have to be obtained in a sequential fashion using RF pulses and magnetic field gradients, such as phase and frequency encoding gradients. Each of the spatially independent receiver coils of the array carries certain spatial information and has a different spatial sensitivity profile. This information is utilized in order to achieve a complete spatial encoding of the received MR signals, for example, by combining the simultaneously acquired data received from each of the separate coils. Parallel MRI techniques allow an undersampling of k-space by reducing the number of acquired phase-encoded k-space sampling lines, while keeping the maximal extent covered in k-space fixed. The combination of the separate MR signals produced by the separate receiver coils enables a reduction of the acquisition time required for an image, in comparison to a conventional k-space data acquisition, by a factor related to the number of the receiver coils. Thus the use of multiple receiver coils acts to multiply imaging speed, without increasing gradient switching rates or RF power.
Two categories of such parallel imaging techniques that have been developed and applied to in vivo imaging are so-called “image space methods” and “k-space methods.” An exemplary image space method is known in the art as sensitivity encoding (“SENSE”), while an exemplary k-space method is known in the art as simultaneous acquisition of spatial harmonics (“SMASH”). With SENSE, the undersampled k-space data is first Fourier transformed to produce an aliased image from each coil, and then the aliased image signals are unfolded by a linear transformation of the superimposed pixel values. With SMASH, the omitted k-space lines are synthesized or reconstructed prior to Fourier transformation, by constructing a weighted combination of neighboring k-space lines acquired by the different receiver coils. SMASH requires that the spatial sensitivity of the coils be determined, and one way to do so is by “autocalibration” that entails the use of variable density k-space sampling.
A more recent advance to SMASH techniques using autocalibration is a technique known as generalized autocalibrating partially parallel acquisitions (“GRAPPA”), as described, for example, in U.S. Pat. No. 6,841,998. With GRAPPA, k-space lines near the center of k-space are sampled at the Nyquist frequency, in comparison to the undersampling employed in the peripheral regions of k-space. These center k-space lines are referred to as the so-called autocalibration signal (“ACS”) lines, which are used to determine the weighting factors that are utilized to synthesize, or reconstruct, the missing k-space lines. In particular, a linear combination of individual coil data is used to create the missing lines of k-space. The coefficients for the combination are determined by fitting the acquired data to the more highly sampled data near the center of k-space.
Another strategy is to use so-called partial k-space echo-planar imaging (“EPI”), in which the number of acquired k-space lines is reduced and a relatively short echo time (“TE”) is used, thereby minimizing signal dropout. The time required to cover k-space can be further reduced by the use of in-plane SENSE or one of its derivatives.
Other methods for decreasing scan time have been developed. For example, methods for the simultaneous acquisition of image data from multiple imaging slice locations, using an array of multiple radio frequency (“RF”) receiver coils, and subsequent separation of the superimposed slices during image reconstruction have be introduced, as described by D. J. Larkman, et al., in “Use of Multicoil Arrays for Separation of Signal from Multiple Slices Simultaneously Excited,” Journal of Magnetic Resonance Imaging, 2001; 13(2):313-317. This method is limited, however, in that the separation of the multiple slices is rendered difficult by the close spatial proximity of the aliased pixels that must be separated during image reconstruction. For example, if image data is acquired from three slices simultaneously, and with an inter-slice spacing of around 3 cm, then aliasing will be present along the slice-encoding direction, and this aliasing must be undone in order to produce reliable images. The origin of the aliased pixels are only 3 cm apart in space, and it is this spatial closeness of the aliased pixels that makes their separation difficult by standard parallel imaging methods, such as sensitivity encoding (“SENSE”).
The difficulties of SENSE, and other similar methods, to properly separate the aliased pixels results from the differences in detection strength among the multiple array coil elements at the locations of the aliased pixels. In particular, the problem is that the detection profiles of the coil array elements are not unique enough on the spatial scale of a few centimeters. As a result, a high level of noise amplification, characterized by a high SENSE g-factor, is present in the separated images. This result is in contrast to the conventional implementation of SENSE methods, in which an undersampled phase encoding scheme produces aliasing along the phase-encoding direction, which is orthogonal to the slice-encoding direction. Moreover, this in-plane aliasing results in pairs of aliased pixels that are separated by one-half of the image field-of-view (“FOV”). For a conventional brain image, the FOV is equal to around 24 cm; thus, when aliasing occurs in the imaging plane, or slice, the distance between aliased pixels is around 12 cm. It is contemplated that it is the four-fold smaller distance between aliased pairs of pixels that results in significant noise amplification in the method disclosed by Larkman. It would therefore be desirable to provide a method for simultaneous multi-slice imaging that is produces less noise amplification than presently available methods, such as the one taught by Larkman.
Another notable method for simultaneous multi-slice imaging was described by D. A. Feinberg, et al., in “Simultaneous Echo Refocusing in EPI,” Magn. Reson. Med., 2002; 48(1):1-5. In this method, which is termed “SER-EPI,” the RF excitation of the slices is sequential, as opposed to truly simultaneous. A readout gradient pulse is applied between two sequential excitations, and acts to shift the k-space data of one slice relative to the other along the kx-direction, which corresponds to the readout direction in image space. By lengthening the readout window, the k-space data for both slices is captured sequentially. The data can then be cut apart and reconstructed separately. This approach has several downsides, however. Since the excitation is not simultaneous, the two slices do not have identical echo times (“TE”). In fact, the TEs typically differ by about 3 ms. This difference in TE is problematic, in that image intensity and contrast is exponentially dependent on TE. Thus, the two slices are not truly identical in image contrast or intensity. Another limitation of the SER-EPI method is that the lengthened readout needed to capture the shifted k-space data of the second slice increases the total readout duration. In turn, this increased duration increases the B0 susceptibility distortions included in the resultant EPI images.
More recently, the SER-EPI method of Feinberg has been modified to include the approach utilized by Larkman, as described by D. A. Feinberg, et al., in “Multiplexed Echo Planar Imaging for Sub-Second Whole Brain fMRI and Fast Diffusion Imaging,” PLos ONE (5):e15710. This more recently modified method, however, still includes the limitations of the reconstruction technique described by Larkman.
Simultaneous multi-slice methods have not gained much traction in conventional imaging since there are alternative parallel imaging methods, such as conventional SENSE and GRAPPA, for accelerating standard image acquisitions. However, as noted above, these methods do not confer the same acceleration benefits on pulse sequences such as EPI as they do on other conventional pulse sequences. Unlike parallel imaging methods such as SENSE and GRAPPA, multi-slice acquisition techniques do not aim to shorten the time spent on reading out k-space data, for example, by reducing the number of phase-encodings. Rather, they aim to acquire signal data from multiple image slice locations per acquisition, such that the number of repetitions of a pulse sequence can be reduced to similarly reduce overall scan time. For example, a three-fold accelerated multi-slice acquisition acquires image data from three image slice locations per each repetition of the EPI sequence. As a result of this simultaneous acquisition, the number of repetitions of an EPI sequence required to cover an imaging volume is reduced, thereby similarly reducing the total acquisition time.
It would therefore be desirable to provide a method for simultaneous, multi-slice imaging that allows for a more reliable separation of aliased pixels than currently available methods for simultaneous multi-slice imaging, so that the benefits associated with these techniques can be realized in a clinical setting. It would further desirable to provide such a method that would be amenable to functional MRI (“fMRI”) techniques, including resting state or functional connectivity fMRI.